Transfer Learning based Location-Aided Modulation Classification in Indoor Environments for Cognitive Radio Applications

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dc.contributor.authorTamizhelakkiya, K.
dc.contributor.authorGauni, S.
dc.contributor.authorChandhar, P.
dc.coverage.issue4cs
dc.coverage.volume32cs
dc.date.accessioned2024-01-09T14:20:53Z
dc.date.available2024-01-09T14:20:53Z
dc.date.issued2023-12cs
dc.description.abstractModulation classification is a crucial technique to utilize the unconsumed spectrum in Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) systems to meet the required traffic demands for future-generation cellular networks. This paper presents an end-to-end experimental setup as a generic methodology to implement various Transfer Learning (TL) models in an indoor environment. This allows us to learn the features from multiple modulation signals to train and test the model. The performance evaluation of proposed TL models such as Convolutional Neural Network-Random Forest (CNN-RF), and Convolutional Long Short Term Deep Neural Network (CLDNN) -Random Forest (CLDNN-RF) have been thoroughly discussed. The result shows that the proposed TL models yield more than 90% classification accuracy for various modulation types. A proposed framework for location-specific TL model selection based on the maximum classification accuracy has been investigated.en
dc.formattextcs
dc.format.extent531-541cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2023 vol. 32, č. 4, s. 531-541. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2023.0531en
dc.identifier.issn1210-2512
dc.identifier.urihttps://hdl.handle.net/11012/244213
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2023/23_04_0531_0541.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectDeep Learning (DL)en
dc.subjectmodulation classificationen
dc.subjectCNNen
dc.subjectSoftware Defined Radio (SDR)en
dc.subjectTransfer Learning (TL)en
dc.titleTransfer Learning based Location-Aided Modulation Classification in Indoor Environments for Cognitive Radio Applicationsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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